Simon Fraser University

Example: Contrasting Univariate and Multivariate Analyses

Consider the two classes indicated by `H' and `O' in Figure 7.1. The results are shown in Figure 7.2. data random; drop n; Group = 'H'; do n = 1 to 20; X = 4.5 + 2 * normal(57391); Y = X + .5 + normal ...
Risk

Modeling multivariate operational losses via copula-based distributions with g-and-h marginals

We propose a family of copula-based multivariate distributions with g-and-h marginals. After studying the properties of the distribution, we develop a two-step estimation strategy and analyze via ...
JSTOR Daily

The Lagrange Distributions and Branching Processes

The supply of explicit analytic forms of interesting multivariate distributions can be enriched by considering multivariate Lagrange distributions which are known to be the distributions of the sizes ...
Risk

Measuring tail operational risk in univariate and multivariate models with extreme losses

This paper considers some univariate and multivariate operational risk models, in which the loss severities are modeled by some weakly tail dependent and heavy-tailed positive random variables, and ...
Simon Fraser University

A Step-by-Step Approach to Using the SAS System for Univariate and Multivariate Statistics

Larry Hatcher, Ph.D. and Edward J. Stepanski, Ph.D. Introduction: The Basics of One-Way ANOVA, Between-Groups Design Example with Significant Differences between Experimental Conditions Understanding ...
JSTOR Daily

Families of Multivariate Distributions Involving the Rosenblatt Construction

Recently, Jones pointed out a useful device for enriching families of univariate distributions. Typically, one may construct a random variable with distribution F by considering F-1 (U), where U is a ...